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Robust Multi-objective Collaborative Optimization of Complex Structures

机译:复杂结构的强大多目标协同优化

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This paper presents a new approach aims to solve robust multidisciplinary design optimization MDO problem called Improved Multi-objective Robust Collaborative Optimization. This method combines the Multi-objective Robust Collaborative Optimization method, the Worst Possible Point constraint cuts and the Genetic algorithm NSGA-II type as an optimizer to solve the robust optimization problem of complex structure named Y-stiffened panel under interval uncertainty. The proposed approach hierarchically decomposes the optimization problem into a structure level considered as an upper level in the Y-stiffened panel and a second level considered as a lower level of the studied panel. A robust multi-objective optimization problem intended to optimize the eigenfrequency, the global mass and the displacement at a fixed point of the Y-stiffened panel at the first level and each structure's robust optimization problem allows optimizing its eigenfrequency and mass limited by their local constraint functions at the second one. Tor demonstrate our method, an engineering example of Y-stiffened panel is treated. A good performance of proposed method is proved by a comparison between obtained results and Non-Distributed Multi-objective Robust Optimization.
机译:本文提出了一种新方法,旨在解决强大的多学科设计优化MD​​O问题,称为改进的多目标稳健协作优化。该方法结合了多目标稳健的协作优化方法,最差可能的点约束切割和遗传算法NSGA-II型作为优化器,以解决在间隔不确定性下以Y-Liffend面板命名的复杂结构的鲁棒优化问题。所提出的方法将优化问题分解成被认为是Y超硬化板中的上层的结构水平,并且被认为是所研究面板的较低水平的第二级。旨在优化在第一级和每个结构的鲁棒优化问题的y-liffened面板的固定点处的特征频率,全局质量和位移,允许优化其当地约束的特征频率和质量限制第二个功能。图案证明了我们的方法,处理了Y超硬化板的工程例。通过所获得的结果和非分布式多目标稳健优化之间的比较证明了所提出的方法的良好表现。

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